Pixel and object-based machine learning classification schemes for lithological mapping enhancement of semi-arid regions using sentinel-2a imagery: a case study of the southern moroccan meseta

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• who: . et al. from the Deptof Geology, Laboratory of Applied Geology, Geomatic and Environment, Faculty of Sciences Ben M'Sik, Hassan II University of Casablanca, King Saud University, Riyadh, Saudi Arabia have published the research work: Pixel and Object-based Machine Learning Classification Schemes for Lithological Mapping Enhancement of Semi-Arid Regions using Sentinel-2A Imagery: A Case Study of the Southern Moroccan Meseta, in the Journal: (JOURNAL) of 29/Oct/2017
• what: This research is intended to analyze and evaluate the efficiency of these three approaches for lithological mapping in semi-arid areas by . . .
  

   

  

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